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Related papers: Gain/Loss of derivatives for complex vector fields

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This is the final part of a series of papers where we study perturbations of divergence form second order elliptic operators $-\operatorname{div} A \nabla$ by first and zero order terms, whose complex coefficients lie in critical spaces,…

Analysis of PDEs · Mathematics 2023-02-07 Simon Bortz , Steve Hofmann , José Luis Luna Garcia , Svitlana Mayboroda , Bruno Poggi

The extended L\"uroth's Theorem says that if the transcendence degree of $\KK(\mathsf{f}_1,\dots,\mathsf{f}_m)/\KK$ is 1 then there exists $f \in \KK(\underline{X})$ such that $\KK(\mathsf{f}_1,\dots,\mathsf{f}_m)$ is equal to $\KK(f)$. In…

Symbolic Computation · Computer Science 2011-11-08 Guillaume Chèze

We examine gradient descent on unregularized logistic regression problems, with homogeneous linear predictors on linearly separable datasets. We show the predictor converges to the direction of the max-margin (hard margin SVM) solution. The…

Machine Learning · Statistics 2024-10-29 Daniel Soudry , Elad Hoffer , Mor Shpigel Nacson , Suriya Gunasekar , Nathan Srebro

We prove mixed weak estimates of Sawyer type for fractional operators. More precisely, let $\mathcal{T}$ be either the maximal fractional function $M_\gamma$ or the fractional integral operator $I_\gamma$, $0<\gamma<n$, $1\leq p<n/\gamma$…

Analysis of PDEs · Mathematics 2017-12-25 Fabio Berra , Marilina Carena , Gladis Pradolini

This article introduces a framework for evaluating statistical decisions under both prior ambiguity and likelihood misspecification. We begin with an ambiguity set - a frequentist model that pairs a possibly misspecified likelihood with…

Econometrics · Economics 2026-05-14 Karun Adusumilli

We study convex empirical risk minimization for high-dimensional inference in binary models. Our first result sharply predicts the statistical performance of such estimators in the linear asymptotic regime under isotropic Gaussian features.…

Statistics Theory · Mathematics 2020-02-27 Hossein Taheri , Ramtin Pedarsani , Christos Thrampoulidis

We consider the problem of evaluating representations of data for use in solving a downstream task. We propose to measure the quality of a representation by the complexity of learning a predictor on top of the representation that achieves…

Machine Learning · Computer Science 2021-02-08 William F. Whitney , Min Jae Song , David Brandfonbrener , Jaan Altosaar , Kyunghyun Cho

Consider nonparametric function estimation under $L^p$-loss. The minimax rate for estimation of the regression function over a H\"older ball with smoothness index $\beta$ is $n^{-\beta/(2\beta+1)}$ if $1\leq p<\infty$ and $(n/\log…

Statistics Theory · Mathematics 2015-02-10 Johannes Schmidt-Hieber

Given an $m$-tuple of weights $\vec{v}=(v_1,\dots,v_m)$, we characterize the classes of pairs $(w,\vec{v})$ involved with the boundedness properties of the multilinear fractional integral operator from…

Classical Analysis and ODEs · Mathematics 2022-05-25 Fabio Berra , Gladis Pradolini , Wilfredo Ramos

Let $\xi$ be an integrable random variable defined on $(\Omega, \mathcal{F}, \mathbb{P})$. Fix $k\in \mathbb{Z}_+$ and let $\{\mathcal{G}_{i}^{j}\}_{1\le i \le n, 1\le j \le k}$ be a reference family of sub-$\sigma$-fields of $\mathcal{F}$,…

Probability · Mathematics 2022-11-07 Stanisław Cichomski , Adam Osękowski

In this paper, we provide conditions under which one can take derivatives of the solution to convex optimization problems with respect to problem data. These conditions are (roughly) that Slater's condition holds, the functions involved are…

Optimization and Control · Mathematics 2019-11-13 Shane Barratt

In this paper we will study the Cauchy problem for strictly hyperbolic operators with low regularity coefficients in any space dimension $N\geq1$. We will suppose the coefficients to be log-Zygmund continuous in time and log-Lipschitz…

Analysis of PDEs · Mathematics 2013-09-19 Ferruccio Colombini , Daniele Del Santo , Francesco Fanelli , Guy Métivier

This paper addresses the study of derivative-free smooth optimization problems, where the gradient information on the objective function is unavailable. Two novel general derivative-free methods are proposed and developed for minimizing…

Optimization and Control · Mathematics 2023-11-29 Pham Duy Khanh , Boris S. Mordukhovich , Dat Ba Tran

We employ techniques from optimal transport in order to prove decay of transfer operators associated to iterated functions systems and expanding maps, giving rise to a new proof without requiring a Doeblin-Fortet (or Lasota-Yorke)…

Dynamical Systems · Mathematics 2015-08-25 Benoit Kloeckner , Artur Lopes , Manuel Stadlbauer

In this paper, we present a new method for estimating the $L_2$-gain of systems governed by 2nd order linear Partial Differential Equations (PDEs) in two spatial variables, using semidefinite programming. It has previously been shown that,…

Optimization and Control · Mathematics 2024-06-18 Declan S. Jagt , Matthew M. Peet

Given a domain above a Lipschitz graph, we establish solvability results for strongly elliptic second-order systems in divergence-form, allowed to have lower-order (drift) terms, with $L^p$-boundary data for $p$ near $2$ (more precisely, in…

Analysis of PDEs · Mathematics 2020-06-25 Martin Dindoš , Marius Mitrea , Sukjung Hwang

We consider several harmonic analysis operators in the multi-dimensional context of the Dunkl Laplacian with the underlying group of reflections isomorphic to $\mathbb{Z}_2^n$ (also negative values of the multiplicity function are…

Classical Analysis and ODEs · Mathematics 2023-10-25 Alejandro J. Castro , Tomasz Z. Szarek

It is well known that elliptic estimates fail for the $\bar\partial$-Neumann problem. Instead, the best that one can hope for is that derivatives in every direction but one can be estimated by the associated Dirichlet form, and when this…

Complex Variables · Mathematics 2022-01-11 Phillip S. Harrington , Andrew Raich

The transport of positive quantities underlies countless physical processes, including fluid, gas, and plasma dynamics. Discretizing the associated partial differential equations with Galerkin methods can result in spurious nonpositivity of…

Numerical Analysis · Mathematics 2025-05-19 Brook Eyob , Florian Schäfer

We study the problem of nonparametric estimation under $\bL_p$-loss, $p\in [1,\infty)$, in the framework of the convolution structure density model on $\bR^d$. This observation scheme is a generalization of two classical statistical models,…

Statistics Theory · Mathematics 2017-04-17 Oleg Lepski , Thomas Willer